How to use the Conditional function in Alteryx

This recipe helps you use the Conditional function in Alteryx

Recipe Objective:-How to use the Conditional function in Alteryx.

Step 1:-

Open Alteryx Designer software.Here New workflow1 is by default available.

Step 2:-

Now go to the Favorite tab or IN/OUT tab where we can see a tool named as "INPUT DATA".

Step 3:-

Drag the INPUT DATA tool on the below side in the New Workflow1.Now go to the Configuration pane/window and click on the drop down available to connect a file or database.

Get Access to Plant Species Identification Project using Machine Learning

Step 4:-

After this it will redirect us to the data connection window, here we have to click on files option, then click on select file option,it will then ask us to select a file from the folder, here we have selected a file named as"Sales 2017-Copy".Then select "50 Records orders" sheet from file and click on Ok.

Step 5:-

Then click on Run button or press CTRL+R, In the results workflow data will be displayed.Drag the Formula tool from the Preparation tab and connect it with the INPUT DATA tool.

Step 6:-

Then go to the configuration pane/window, click on "+" sign so a new expression window will be opened.First select the option as "+Add column" from output column drop down, name the new column as "Sales Done" or if its already added select it .In the expression window type "Round([Sales Done],2)", the data type will be "Double" then click on Run button, the round of values will be displayed in the results workflow under the sales done field/column.

Step 7:-

Now go to to the results workflow, click on the 3 dots available at the Sales Done field/column, then sort the data in descending order (higher to lower).Then go to the configuration pane/window, click on "+" sign so a new expression window will be opened.First select the option as "+Add column" from output column drop down, name the new column as "Sales Type".In the expression window type the Condition "If [Sales Done]> 500 then "High Sales" else "Low Sales" endif", the data type will be "V_WString" then click on Run button, the results workflow will be available under the sales type field/column.

What Users are saying..

profile image

Ameeruddin Mohammed

ETL (Abintio) developer at IBM
linkedin profile url

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good... Read More

Relevant Projects

Image Classification Model using Transfer Learning in PyTorch
In this PyTorch Project, you will build an image classification model in PyTorch using the ResNet pre-trained model.

Build a Multi Touch Attribution Machine Learning Model in Python
Identifying the ROI on marketing campaigns is an essential KPI for any business. In this ML project, you will learn to build a Multi Touch Attribution Model in Python to identify the ROI of various marketing efforts and their impact on conversions or sales..

Locality Sensitive Hashing Python Code for Look-Alike Modelling
In this deep learning project, you will find similar images (lookalikes) using deep learning and locality sensitive hashing to find customers who are most likely to click on an ad.

Build a Collaborative Filtering Recommender System in Python
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.

Deploy Transformer-BART Model on Paperspace Cloud
In this MLOps Project you will learn how to deploy a Tranaformer BART Model for Abstractive Text Summarization on Paperspace Private Cloud

AI Video Summarization Project using Mixtral, Whisper, and AWS
In this AI Video Summarization Project, you will build a quiz generation tool by extracting key concepts from educational videos and generating concise summaries.

Learn to Build a Siamese Neural Network for Image Similarity
In this Deep Learning Project, you will learn how to build a siamese neural network with Keras and Tensorflow for Image Similarity.

Machine Learning project for Retail Price Optimization
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

Build a Autoregressive and Moving Average Time Series Model
In this time series project, you will learn to build Autoregressive and Moving Average Time Series Models to forecast future readings, optimize performance, and harness the power of predictive analytics for sensor data.

GCP MLOps Project to Deploy ARIMA Model using uWSGI Flask
Build an end-to-end MLOps Pipeline to deploy a Time Series ARIMA Model on GCP using uWSGI and Flask